Abstract
With the rapid development of urban economy and the continuous expansion of urban scale, the limitations of urban carrying capacity begin to appear. For the sustainable development of the city, more and more scholars are paying attention to the research onurban carrying capacity. Basedon the continuous research of the authors’ research group over the past ten years, this paper uses a multiscale geographically weighted regression model and method to explore the impact of geographical location, floor area ratio, public transportation, residents’ consumption level, the density of high-tech enterprises, and the ecological environment on the carrying capacity of the Shanghai metropolis. The results show that (1) the impact of geographical location on the bearing capacity decreases from downtown to the outer areas and from the northeastern area to the southwestern area of Shanghai. (2) On the whole, the elasticity of the average floor area ratio to the urban carrying capacity is 0.52%. In different regions, most of the central urban areas have exceeded the optimal average plot ratio. With an increase in the average plot ratio, the urban carrying capacity presents a downward trend. Other sample areas generally did not reach the average optimal plot ratio, especially the southwestern area of Shanghai. With an increase in the average plot ratio, the urban carrying capacity of this area improved significantly. (3) The elasticity of public transportation convenience to the urban carrying capacity is 0.23%; that is, the average increase in the urban carrying capacity is 0.23% for every 1% increase in public transportation convenience. The elasticity of residents’ consumption level is −0.18%; in other words, every 1% increase in residents’ consumption level will reduce the urban carrying capacity by 0.18% on average. The elasticity of the density of high-tech enterprises is 0.08%; hence, when the density of high-tech enterprises increases by 1%, the urban carrying capacity increases by 0.08% on average. Lastly, the elasticity of the eco-environmental status index is 0.17%; that is, every 1% increase in the eco-environmental status index increases the urban carrying capacity by 0.17% on average.
Highlights
Shanghai the capacity northeastern areas southwestern location. This structure is consistent with our perception of Shanghai, because generally have excellent historical and cultural heritage and easy access to medical the central urban area of Shanghai and the northeastern areas generally have excellent treatment
In terms of the effect of the model, multiscale geographically weighted regression solves the defect whereby traditional regression models must assume that the factors are spatially stable and have the same influence scale
In terms of the accuracy of the model, the goodness of fit of the multiscale geographically weighted regression is 0.92, which is more explanatory than the spatial error model
Summary
With the rapid development of industrialization and urbanization, a large number of rural people have flooded into cities, the scale of urban construction land has continued to expand, and the resource and environmental constraints of large cities are becoming increasingly prominent. In Shanghai, with the continuous improvement of land development intensity, the expansion of construction land over many years has rendered the urban ecological space and public space obviously insufficient. The separation of jobs from housing and residents’ long-distance commuting have caused serious traffic congestion in the morning and evening rush hours. Environmental problems, such as poor air and water quality and garbage sieges still need to be further improved. The spatial distribution of industries, cities and people is unbalanced, and the urban spatial structure needs to be optimized
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